Method for automatically predicting treatment management factor characteristics of disease and electronic apparatus

Abstract

The present application disclosed a method for automatically predicting treatment management factor characteristics and an electronic apparatus, the method includes: acquiring, by the electronic apparatus, concerted effect burden parameter data of several mutant genes of a tested sample of a target object on expression activity of each gene in a predetermined genome, wherein the predetermined genome corresponds to the disease; and outputting, by the electronic apparatus, predictive data of at least one treatment management factor characteristic of the target object relative to the disease based on the concerted effect burden parameter data.

1 . A method for automatically predicting treatment management factor characteristics of a disease, executed by an electronic apparatus, and comprising:
 acquiring, by the electronic apparatus, concerted effect burden parameter data of several mutant genes of a tested sample of a target object on expression activity of each gene in a predetermined genome, wherein the predetermined genome corresponds to the disease; and   outputting, by the electronic apparatus, predictive data of at least one treatment management factor characteristic of the target object relative to the disease based on the concerted effect burden parameter data.   
     
     
         2 . The method of  claim 1 , wherein the at least one treatment management factor characteristic of the target object relative to the disease comprises survival characteristics, pathophysiological characteristics, and/or or clinical intervention effects of the target object with the disease. 
     
     
         3 . The method of  claim 1 , wherein the step of outputting predictive data of at least one treatment management factor characteristic of the target object relative to the disease based on the concerted effect burden parameter data comprises:
 comparing the concerted effect burden data of the target object with a preset concerted effect burden-survival mode model of the disease, and acquiring and outputting a survival mode label of the target object relative to the disease.   
     
     
         4 . The method of  claim 3 , wherein:
 the concerted effect burden-survival mode model at least comprises a first survival mode label, a second survival mode label and a preset threshold;   the step of comparing the concerted effect burden data of the target object with a preset concerted effect burden-survival mode model of the disease, and acquiring and outputting a survival mode label of the target object relative to the disease comprises:   comparing the concerted effect burden data of the target object with preset threshold of the concerted effect burden-survival mode model of the disease, outputting, if the concerted effect burden data of the target object reaches the preset threshold, the first survival mode label, and outputting, if the concerted effect burden data of the target object is less than the preset threshold, the second survival mode label.   
     
     
         5 . The method of  claim 4 , wherein the preset threshold of the concerted effect burden-survival mode model of the disease is determined based on concerted effect burden data of several modeling samples, and the several modeling samples are acquired from several patients suffering from the disease. 
     
     
         6 . The method of  claim 5 , wherein the several modeling samples are from several patients suffering from the disease and at a specified evolutionary stage of the disease. 
     
     
         7 . The method of  claim 1 , wherein the step of outputting predictive data of at least one treatment management factor characteristic of the target object relative to the disease based on the concerted effect burden parameter data comprises:
 outputting predictive data of the target object relative to the predetermined treatment management factor characteristics based on the concerted effect burden data of the target object, concerted effect burden data of several pre-acquired modeling samples, and measured data of the predetermined treatment management factor characteristics, wherein the several modeling samples are from several patients suffering from the disease.   
     
     
         8 . The method of  claim 1 , wherein the concerted effect burden parameter of the expression activities of the several mutant genes of the tested sample of the target object to genes in the predetermined genome comprises:
 a number of genes whose expression activity is influenced by the several mutant genes and meets a preset conditions among the genes in the predetermined genome; and/or   a sum of absolute values, a median, a maximum value, and/or a variance, etc. of values in data of the concerted effect parameters; and/or   acquiring at least two simple data of the concerted effect parameters for describing the data of the concerted effect parameters; and acquiring composite data of the concerted effect parameters based on the at least two simple data of the concerted effect parameters.   
     
     
         9 . The method of  claim 1 , wherein the step of acquiring concerted effect burden parameter data of several mutant genes of a tested sample of a target object on expression activity of each gene in a predetermined genome comprises:
 for the genes in the predetermined genome, acquiring concerted effect parameter data of the several mutant genes on expression activity of each gene;   performing noise reduction processing on the concerted effect parameter data of the several mutant genes on expression activity of each gene; and   acquiring the concerted effect burden parameter data of the several mutant genes on expression activity of each gene in the predetermined genome based on a result of performing the noise reduction processing.   
     
     
         10 . An electronic apparatus, comprising: a memory, a processor and a program stored in the memory, wherein the program is configured to be executed by the processor, and when the processor executes the program, a method for automatically predicting treatment management factor characteristics of a disease as claimed is implemented, and the processor is configured for:
 acquiring concerted effect burden parameter data of several mutant genes of a tested sample of a target object on expression activity of each gene in a predetermined genome, wherein the predetermined genome corresponds to the disease; and   outputting predictive data of at least one treatment management factor characteristic of the target object relative to the disease based on the concerted effect burden parameter data.   
     
     
         11 . The method of  claim 2 , wherein the step of acquiring concerted effect burden parameter data of several mutant genes of a tested sample of a target object on expression activity of each gene in a predetermined genome comprises:
 for the genes in the predetermined genome, acquiring concerted effect parameter data of the several mutant genes on expression activity of each gene;   performing noise reduction processing on the concerted effect parameter data of the several mutant genes on expression activity of each gene; and   acquiring the concerted effect burden parameter data of the several mutant genes on expression activity of each gene in the predetermined genome based on a result of performing the noise reduction processing.   
     
     
         12 . The method of  claim 3 , wherein the step of acquiring concerted effect burden parameter data of several mutant genes of a tested sample of a target object on expression activity of each gene in a predetermined genome comprises:
 for the genes in the predetermined genome, acquiring concerted effect parameter data of the several mutant genes on expression activity of each gene;   performing noise reduction processing on the concerted effect parameter data of the several mutant genes on expression activity of each gene; and   acquiring the concerted effect burden parameter data of the several mutant genes on expression activity of each gene in the predetermined genome based on a result of performing the noise reduction processing.   
     
     
         13 . The method of  claim 4 , wherein the step of acquiring concerted effect burden parameter data of several mutant genes of a tested sample of a target object on expression activity of each gene in a predetermined genome comprises:
 for the genes in the predetermined genome, acquiring concerted effect parameter data of the several mutant genes on expression activity of each gene;   performing noise reduction processing on the concerted effect parameter data of the several mutant genes on expression activity of each gene; and   acquiring the concerted effect burden parameter data of the several mutant genes on expression activity of each gene in the predetermined genome based on a result of performing the noise reduction processing.   
     
     
         14 . The method of  claim 5 , wherein the step of acquiring concerted effect burden parameter data of several mutant genes of a tested sample of a target object on expression activity of each gene in a predetermined genome comprises:
 for the genes in the predetermined genome, acquiring concerted effect parameter data of the several mutant genes on expression activity of each gene;   performing noise reduction processing on the concerted effect parameter data of the several mutant genes on expression activity of each gene; and   acquiring the concerted effect burden parameter data of the several mutant genes on expression activity of each gene in the predetermined genome based on a result of performing the noise reduction processing.   
     
     
         15 . The method of  claim 6 , wherein the step of acquiring concerted effect burden parameter data of several mutant genes of a tested sample of a target object on expression activity of each gene in a predetermined genome comprises:
 for the genes in the predetermined genome, acquiring concerted effect parameter data of the several mutant genes on expression activity of each gene;   performing noise reduction processing on the concerted effect parameter data of the several mutant genes on expression activity of each gene; and   acquiring the concerted effect burden parameter data of the several mutant genes on expression activity of each gene in the predetermined genome based on a result of performing the noise reduction processing.   
     
     
         16 . The method of  claim 7 , wherein the step of acquiring concerted effect burden parameter data of several mutant genes of a tested sample of a target object on expression activity of each gene in a predetermined genome comprises:
 for the genes in the predetermined genome, acquiring concerted effect parameter data of the several mutant genes on expression activity of each gene;   performing noise reduction processing on the concerted effect parameter data of the several mutant genes on expression activity of each gene; and   acquiring the concerted effect burden parameter data of the several mutant genes on expression activity of each gene in the predetermined genome based on a result of performing the noise reduction processing.   
     
     
         17 . The method of  claim 2 , wherein the concerted effect burden parameter of the expression activities of the several mutant genes of the tested sample of the target object to genes in the predetermined genome comprises:
 a number of genes whose expression activity is influenced by the several mutant genes and meets a preset conditions among the genes in the predetermined genome; and/or   a sum of absolute values, a median, a maximum value, and/or a variance, etc. of values in data of the concerted effect parameters; and/or   acquiring at least two simple data of the concerted effect parameters for describing the data of the concerted effect parameters; and acquiring composite data of the concerted effect parameters based on the at least two simple data of the concerted effect parameters.   
     
     
         18 . The method of  claim 3 , wherein the concerted effect burden parameter of the expression activities of the several mutant genes of the tested sample of the target object to genes in the predetermined genome comprises:
 a number of genes whose expression activity is influenced by the several mutant genes and meets a preset conditions among the genes in the predetermined genome; and/or   a sum of absolute values, a median, a maximum value, and/or a variance, etc. of values in data of the concerted effect parameters; and/or   acquiring at least two simple data of the concerted effect parameters for describing the data of the concerted effect parameters; and acquiring composite data of the concerted effect parameters based on the at least two simple data of the concerted effect parameters.   
     
     
         19 . The method of  claim 4 , wherein the concerted effect burden parameter of the expression activities of the several mutant genes of the tested sample of the target object to genes in the predetermined genome comprises:
 a number of genes whose expression activity is influenced by the several mutant genes and meets a preset conditions among the genes in the predetermined genome; and/or   a sum of absolute values, a median, a maximum value, and/or a variance, etc. of values in data of the concerted effect parameters; and/or   acquiring at least two simple data of the concerted effect parameters for describing the data of the concerted effect parameters; and acquiring composite data of the concerted effect parameters based on the at least two simple data of the concerted effect parameters.   
     
     
         20 . The method of  claim 5 , wherein the concerted effect burden parameter of the expression activities of the several mutant genes of the tested sample of the target object to genes in the predetermined genome comprises:
 a number of genes whose expression activity is influenced by the several mutant genes and meets a preset conditions among the genes in the predetermined genome; and/or   a sum of absolute values, a median, a maximum value, and/or a variance, etc. of values in data of the concerted effect parameters; and/or   acquiring at least two simple data of the concerted effect parameters for describing the data of the concerted effect parameters; and acquiring composite data of the concerted effect parameters based on the at least two simple data of the concerted effect parameters.